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Purpose

– A design procedure for multi-layer absorbers based on carbon nanotubes (CNT) frequency selective surfaces (FSS) sheets is here developed. The paper aims to discuss there issues.

Design/methodology/approach

– Single layer FSS are first analyzed via finite element (FE). Then equivalent sheets admittances are extracted in a transmission line model. Neural networks (NNs) interpolation over this data and subsequent multi-objective genetic algorithm (GA) based optimizations are then performed to design multiple layers absorbing structures. Designs are finally validated via full wave FEM simulations.

Findings

– In this paper, some absorbing structures made of three or four FSS sheets with total thicknesses around 6 mm are synthesized.

Research limitations/implications

– NNs' accuracy used in the equivalent model can be refined with further training.

Practical implications

– Low profile absorbing materials are of relevant industrial interest both for radar cloaking and anechoic chambers.

Originality/value

– The transmission line model combined with NNs and GA optimization is capable of speeding up the design procedure with respect to a conventional full-wave FEM approach.

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